set -x
export VLLM_ASCEND_ENABLE_NZ=0

MODEL_ID=${MODEL_ID:-Qwen/Qwen2.5-0.5B-Instruct}  # TODO: change to Qwen3-0.6B when CI server is ready
MODEL_PATH=${MODEL_PATH:-${HOME}/.cache/models/${MODEL_ID}}

python3 -m verl.trainer.main_ppo \
    algorithm.adv_estimator=gae \
    data.train_files=$HOME/data/gsm8k/train.parquet \
    data.val_files=$HOME/data/gsm8k/test.parquet \
    data.train_batch_size=16 \
    data.max_prompt_length=512 \
    data.max_response_length=128 \
    data.shuffle=False \
    actor_rollout_ref.model.path="${MODEL_PATH}" \
    actor_rollout_ref.model.use_remove_padding=True \
    actor_rollout_ref.model.enable_gradient_checkpointing=True \
    actor_rollout_ref.actor.optim.lr=1e-6 \
    actor_rollout_ref.actor.ppo_mini_batch_size=8 \
    actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=1 \
    actor_rollout_ref.actor.fsdp_config.param_offload=True \
    actor_rollout_ref.actor.fsdp_config.optimizer_offload=True \
    actor_rollout_ref.actor.use_kl_loss=False \
    actor_rollout_ref.actor.ulysses_sequence_parallel_size=2 \
    actor_rollout_ref.actor.use_dynamic_bsz=True \
    actor_rollout_ref.actor.use_torch_compile=False \
    actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=1 \
    actor_rollout_ref.rollout.tensor_model_parallel_size=1 \
    actor_rollout_ref.rollout.name=vllm \
    actor_rollout_ref.rollout.gpu_memory_utilization=0.8 \
    actor_rollout_ref.rollout.log_prob_use_dynamic_bsz=True \
    actor_rollout_ref.rollout.enable_chunked_prefill=True \
    actor_rollout_ref.rollout.enforce_eager=False \
    critic.optim.lr=1e-5 \
    critic.model.use_remove_padding=True \
    critic.model.path="${MODEL_PATH}" \
    critic.model.enable_gradient_checkpointing=True \
    critic.ppo_micro_batch_size_per_gpu=1 \
    critic.ulysses_sequence_parallel_size=2 \
    critic.model.fsdp_config.param_offload=True \
    critic.model.fsdp_config.optimizer_offload=True \
    critic.use_dynamic_bsz=True \
    trainer.critic_warmup=0 \
    trainer.logger='["console"]' \
    trainer.project_name='verl_ppo_example_gsm8k_qwen3' \
    trainer.experiment_name='qwen3_06b_fsdp' \
    trainer.n_gpus_per_node=8 \
    trainer.nnodes=1 \
    trainer.save_freq=-1 \
    trainer.test_freq=-1 \
    trainer.total_epochs=1 \
    trainer.total_training_steps=1 \
    trainer.device=npu $@
